Concept

Road traffic safety

Related publications (284)

Social-Transmotion: Promptable Human Trajectory Prediction

Alexandre Massoud Alahi, Yang Gao, Kaouther Messaoud Ben Amor, Saeed Saadatnejad

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

2024

In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. ...

Springernature2024

A WIM-Based Assessment of Multiple Vehicle Presence Effects on Fatigue Damage of Highway Bridges

Alain Nussbaumer, Scott Walbridge, Matthew James Sjaarda

The fatigue provisions for bridge design in North America and Europe are highly simplified for the sake of practical implementation, in comparison with the state of the art in understanding of the true fatigue behavior. Historically, one significant simpli ...

2024

Modeling Mode-Dependent Lane Discipline in Hybrid Traffic

Nikolaos Geroliminis, Georgios Anagnostopoulos

Complex interactions can be observed in hybrid transportation systems, where cars share the same road space with other modes such as motorcycles, bicycles or even e-scooters. In this work we further built upon the concept of mode dependent lane discipline. ...

2024

Detecting Road Obstacles by Erasing Them

Pascal Fua, Mathieu Salzmann, Krzysztof Maciej Lis, Sina Honari

Vehicles can encounter a myriad of obstacles on the road, and it is impossible to record them all beforehand to train a detector. Instead, we select image patches and inpaint them with the surrounding road texture, which tends to remove obstacles from thos ...

2024

Artificial Intelligence for road quality assessment in smart cities: a machine learning approach to acoustic data analysis

Simon Elias Bibri

In smart cities, ensuring road safety and optimizing transportation efficiency heavily relies on streamlined road condition monitoring. The application of Artificial Intelligence (AI) has notably enhanced the capability to detect road surfaces effectively. ...

London2023

From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems

Zhixiong Jin

We propose a novel system leveraging deep learning-based methods to predict urban traffic accidents and estimate their severity. The major challenge is the data imbalance problem in traffic accident prediction. The problem is caused by numerous zero values ...

Basel2023

Cycling and walking as means of transport - current review of the research

Vincent Kaufmann, Sonia Monique Curnier, Renate Albrecher

Recent surveys by the Mobile Lives Forum show that around 30% of the French population live locally, yet many trips under 5 km are made by car. There is therefore huge potential for a modal shift to active modes of transport (Kaufmann et al. 2020, Héran 20 ...

EPFL2023

Pedestrian Crossings as a Means of Reducing Conflicts between Cyclists and Pedestrians in Shared Spaces

Evangelos Paschalidis

One significant and simultaneously interesting problem in urban mobility has to do with the study of shared spaces where various categories of users coexist and act together. This paper aims to examine the behavior and preferences of pedestrians and cyclis ...

2023

Haptics based multi-level collaborative steering control for automated driving

Hannes Bleuler, Jürg Alexander Schiffmann, Tomohiro Nakade, Robert Fuchs

Increasing the capability of automated driving vehicles is motivated by environmental, productivity, and traffic safety benefits. But over-reliance on the automation system is known to cause accidents. The role of the driver cannot be underestimated as it ...

2023

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.